What it sells
AI-native materials discovery powered by unpublished experimental data
Business model breakdown
Buyer: who owns the budget?
UnverifiedIndustrial R&D and materials leaders (industry discovery contracts) and university research offices (partnerships).
Trigger: what makes them buy now?
Over 85% of experimental data is discarded unpublished; the site claims $100B+ of R&D value lost yearly and wants to bring new materials to market faster and cheaper.
Workflow: what inputs become what output?
Capture and structure lab data (voice notes to instrument output) in the Dalton platform, build a queryable agentic record of experiments including failures, propose optimized process conditions, then move to papers, patents and scale-up.
Economics: what it saves and how it charges
Discovery contracts with industry and university partnerships; claims under 6 weeks from a partner data set to a first new material discovered.
Distribution: how it reaches customers
Partner-led: "Scope a discovery contract" for industry and "University partnerships" for academia.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Summer 2026 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.